An approach to find influencers analyzing complex social network
This thesis report is submitted in partial fulfilment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2017.
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| Định dạng: | Luận văn |
| Ngôn ngữ: | English |
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BARC University
2018
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| Truy cập trực tuyến: | http://hdl.handle.net/10361/9029 |
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10361-90292022-01-26T07:38:48Z An approach to find influencers analyzing complex social network Chaki, Dipankar Zaber, Dr. Moinul Islam Department of Computer Science and Engineering, BRAC University Complex social network Betweenness centrality Degree centrality Closeness centrality Social network analysis This thesis report is submitted in partial fulfilment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis report. Includes bibliographical references (pages 33-35). Popularity of social media in Bangladesh is prodigious. 80 percent of internet users are on social networking websites like Facebook, Twitter. That is over 16 million people and counting. The rate of new Facebook users is outpacing the country’s birth rate as one new Bangladeshi Facebook account is opened every 20 seconds. This makes social media a great platform for government to reach out to citizens and stay up-to-date with current events and trends in society. That is why, a Facebook group named “Public Service Innovation Bangladesh” has been created. In this group, discussions related to public service innovation, public service related problems and solutions, decision making in administrative works etc. are being prioritized. The focus of this study is to construct complex network from posts given by the members of this Facebook group, analyze features of the complex network including degree distribution, assortative mixing and betweenness centrality. It is important to detect influencers of that Facebook group. We have analyzed group data from January 1, 2016 to June 30, 2017 and generated a report which has given some interesting insights about that group. During this time frame, 5183 posts have been posted and most amazingly, majority of these posts have been posted from November, 2016 to till date. So, it can be said that, this group is growing now. In our constructed network, we have seen that the people who give more posts, get more likes and comments. That is how, they tend to be connected with other highly connected people. If a person who has many connections, gives a post, gets more attention meaning likes and comments than other. Our study helps to understand the structure of this group and finds the influencers of the group. Index Terms: Complex Network Analysis, Social Network Analysis, Betweenness Centrality, Closeness Centrality, Degree Centrality, Characteristics Path Length Dipankar Chaki M. Computer Science and Engineering 2018-01-11T08:51:13Z 2018-01-11T08:51:13Z 2017 2017-07 Thesis ID 15166004 http://hdl.handle.net/10361/9029 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 39 pages application/pdf BARC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Complex social network Betweenness centrality Degree centrality Closeness centrality Social network analysis |
| spellingShingle |
Complex social network Betweenness centrality Degree centrality Closeness centrality Social network analysis Chaki, Dipankar An approach to find influencers analyzing complex social network |
| description |
This thesis report is submitted in partial fulfilment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2017. |
| author2 |
Zaber, Dr. Moinul Islam |
| author_facet |
Zaber, Dr. Moinul Islam Chaki, Dipankar |
| format |
Thesis |
| author |
Chaki, Dipankar |
| author_sort |
Chaki, Dipankar |
| title |
An approach to find influencers analyzing complex social network |
| title_short |
An approach to find influencers analyzing complex social network |
| title_full |
An approach to find influencers analyzing complex social network |
| title_fullStr |
An approach to find influencers analyzing complex social network |
| title_full_unstemmed |
An approach to find influencers analyzing complex social network |
| title_sort |
approach to find influencers analyzing complex social network |
| publisher |
BARC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/9029 |
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AT chakidipankar anapproachtofindinfluencersanalyzingcomplexsocialnetwork AT chakidipankar approachtofindinfluencersanalyzingcomplexsocialnetwork |
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1814309762835152896 |